A virtual debugging and simulation method for industrial robots based on digital twins

Abstract

The present invention provides an industrial robot virtual debugging and simulation method based on digital twins, comprising the following steps: S1: establishing a digital twin model of the industrial robot; S2: establishing a kinematic model of the industrial robot, and performing forward kinematic analysis and inverse kinematic analysis on the established kinematic model; S3: associating the digital twin model established in step S1 with the industrial robot signal, performing virtual debugging and digital twin virtual-reality mapping; S4: the industrial robot realizes digital twin visualization, that is, establishing a digital twin model that is highly consistent with the actual robot and its working environment in a virtual environment, and establishing real-time communication between the two, thereby realizing comprehensive debugging of the actual robot and its peripheral equipment in the virtual environment, and mapping the state of the actual robot to the digital twin model, realizing comprehensive simulation of the actual robot and its operating state, and effectively improving the accuracy and adaptability of industrial robot simulation.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robot debugging and simulation, and in particular to an industrial robot virtual debugging and simulation method based on digital twins. Background Art

[0002] The integration of next-generation information technology and manufacturing has made intelligent automation a major trend in the manufacturing industry. Industrial robots offer greater cost-effectiveness in terms of flexibility, repeatability, and support for new functions, effectively improving production efficiency and product quality. They have become a symbol of automation and intelligent manufacturing.

[0003] Currently, there are two programming modes for robots: online and offline. Online programming consumes the robot's actual working time and requires manual instruction, resulting in lower overall efficiency and poorer accuracy. Therefore, online programming is no longer suitable for the current manufacturing industry. Offline programming constructs a three-dimensional model of the robot and its work environment in a virtual environment. In offline simulation, a simulation environment is established, the program is generated, and then transferred to the physical system. Offline programming separates the actual robot system environment from the programming environment, avoiding safety hazards in some dangerous scenarios. Compared to online programming, offline programming does not occupy production resources and also saves labor costs.

[0004] However, because the real and virtual worlds are independent of each other, information about the actual robot cannot be fed back to the virtual simulation system in real time. Similarly, if robot-related data is modified in the virtual environment, it cannot be quickly synchronized to the real scene. Moreover, if the production line changes, re-planning the workflow is very costly. Summary of the Invention

[0005] The present invention discloses a virtual debugging and simulation method for industrial robots based on digital twins, which solves the problem that the real space and virtual space information are independent of each other during offline programming, making it impossible to feed back the actual robot-related information to the virtual simulation system in real time; and the robot-related data modified in the virtual space cannot be quickly synchronized to the actual robot. A digital twin model that is highly consistent with the actual robot and its working environment is established in the virtual environment, and real-time communication is established between the two, thereby realizing comprehensive debugging of the actual robot and its peripheral equipment in the virtual environment, and mapping the status of the actual robot to the digital twin model, realizing comprehensive simulation of the actual robot and its operating status, and effectively improving the accuracy and adaptability of industrial robot simulation.

[0006] To achieve the above object, the technical solution of the present invention is specifically implemented as follows:

[0007] The present invention discloses a virtual debugging and simulation method for an industrial robot based on digital twin, comprising the following steps:

[0008] step:

[0009] S1: Build a digital twin model of an industrial robot;

[0010] S2: Establish a kinematic model of the industrial robot and perform forward kinematics analysis and inverse kinematics analysis on the established kinematic model;

[0011] S3: Associating the digital twin model of the industrial robot established in step S1 with the industrial robot signal to perform virtual debugging and digital twin virtual-reality mapping;

[0012] S4: Industrial robots realize digital twin visualization.

[0013] Furthermore, the specific implementation of step S1 is:

[0014] Directly import the industrial robot model or build a model based on the actual geometric dimensions of the industrial robot;

[0015] The geometric model is set to have the same material, color, shape and structural relationship as the industrial robot, so that the generated digital twin model has a visual and structural twin relationship with the industrial robot.

[0016] Furthermore, the forward kinematics analysis in step S2 is specifically implemented as follows:

[0017] Forward kinematics analysis is to determine the position of the end effector when the joint angle, link length and combination of the robot are determined. The position of the end effector is determined by the homogeneous transformation matrix The specific expression is:

[0018]

[0019] in, Represents the poses of the six joint coordinate systems relative to the base coordinate system; Indicates the relative relationship between the i-th joint and the i-1 joint coordinate system; (n x ,n y ,n z ) represents the x-axis direction of the end effector coordinate system; (o x ,o y ,o z ) represents the y-axis direction of the end effector coordinate system; (a x ,a y ,a z ) represents the z-axis direction of the end effector coordinate system; (p x ,p y ,pz ) represents the position of the end effector;

[0020] Use connecting rod length a i , connecting rod torsion angle α i , connecting rod offset d i , joint angle θ i Four parameters are used to describe the relative relationship between two adjacent rods, specifically: d i is the distance from the origin of the i-1 coordinate system to Z i-1 Axis and X i The intersection of the axes along the Z i-1 The distance measured along the axis; a i is the length of the common normal between the axis of joint i and the axis of joint i+1; α i The axis of joint i and the axis of joint i+1 are at the axis of joint i and a i The angle on the plane; θ i For Z i-1 Axis X i-1 Axis steering X i The joint angles of the axes, where i = 1, 2, ..., 6; the initial value represents the angles of each joint in the initial state of the industrial robot;

[0021] Through the above definition, the transformation relationship is expressed as a matrix express:

[0022]

[0023] Among them, Trans(X,l) represents translation transformation, that is, translation l units along the positive direction of the X axis; Rot(X,θ) represents rotation transformation, that is, rotation angle θ around the positive direction of the X axis;

[0024] Combine equations (1) and (2) to obtain the pose matrix of the end effector at the key point:

[0025] Furthermore, the inverse kinematics analysis in step S2 is specifically implemented as follows:

[0026] Inverse kinematics refers to the pose matrix of the end effector Reverse solve the angle θ of each joint i (i=1,2,…,6);

[0027] Separate the expressions of the position and posture of the industrial robot, specifically:

[0028] Multiply the first three joint coordinate system transformation matrices in equation (1) by the left side:

[0029]

[0030] The matrices on both sides of equation (3) are divided into blocks and equalized to obtain the equation system:

[0031]

[0032] Among them, s i = sinθ i , c i =cosθ i ,s ij = sin(θ i +θ j )c ij =cos(θ i +θ j )(i=1,2,…,6)(j=1,2,…,6);

[0033] The arctan2(y / x) function is introduced to solve θ in equation (4) to obtain all 8 groups of solutions for the six joint angles:

[0034] Since the equations in formula (4) can be expressed as follows:

[0035] asinθ i +bcosθ i =c (5)

[0036] If a, b, c are continuous in this formula, and only if inequality a 2 +b 2 >c 2 When this is true, the equation has a solution:

[0037]

[0038] Combining equations (4), (5), and (6), we can obtain all 8 groups of solutions.

[0039] Furthermore, the principle for obtaining the optimal solution among the 8 groups of solutions obtained is:

[0040]

[0041] Among them, θ ij represents the jth group of solutions for the i-th joint, θ i ′ represents the angle of the i-th joint at the previous point.

[0042] Furthermore, the specific implementation of step S3 includes:

[0043] By using process simulation methods, the digital twin model is given process attributes, so that each process action of the industrial robot digital twin model has corresponding motion process logic;

[0044] Use the timing editor to simulate the process attributes of the industrial robot and plan the timing relationship of each process according to the timing table of the action process;

[0045] Achieve synchronous mapping between industrial robots and their digital twin models:

[0046] Establish real-time communication between industrial robots and their digital twins;

[0047] When the control unit of the industrial robot serves as the communication server, virtual reality is reflected in the real world: the industrial robot transmits its joint data to its digital twin model in real time, and its digital twin model receives the joint data transmitted by the industrial robot and applies steps S1 and S2 to achieve synchronous motion.

[0048] When the control unit of the digital twin model is used as the communication server, virtual control of the real is achieved: the digital twin model sends control instructions to the control unit of the industrial robot, and the industrial robot receives and executes the control instructions.

[0049] Furthermore, the timing simulation of industrial robots is a time-based simulation.

[0050] Beneficial technical effects:

[0051] The present invention discloses a virtual debugging and simulation method for an industrial robot based on digital twins, which specifically includes the following steps: S1: establishing a digital twin model of the industrial robot; S2: establishing a kinematic model of the industrial robot, and performing forward kinematic analysis and inverse kinematic analysis on the established kinematic model; S3: associating the digital twin model of the industrial robot established in step S1 with the industrial robot signal, and performing virtual debugging and digital twin virtual-reality mapping; S4: the industrial robot realizes digital twin visualization, that is, establishing a digital twin model that is highly consistent with the actual robot and its working environment in a virtual environment, and establishing real-time communication between the two, so as to realize comprehensive debugging of the actual robot and its peripheral equipment in the virtual environment, and at the same time mapping the state of the actual robot to the digital twin model, realizing comprehensive simulation of the actual robot and its operating state, and effectively improving the accuracy and adaptability of industrial robot simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for describing the embodiments.

[0053] Figure 1 This is a flowchart of the specific steps of the virtual debugging and simulation method of an industrial robot based on digital twins described in the present invention;

[0054] Figure 2 This is the spatial structure diagram of a six-degree-of-freedom industrial robot;

[0055] Figure 3 : This is a diagram showing the relationship between the connecting rod joint axes of an industrial robot in an embodiment of the present invention;

[0056] Figure 4 A software cross-sectional diagram of the Home point setting of an industrial robot in an embodiment of the present invention;

[0057] Figure 5 This is a timing chart of the industrial robot's motion process in an embodiment of the present invention;

[0058] Figure 6 This is a flow chart of industrial robot signal connection in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0060] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0061] It should be noted that the working environment composed of components, control units and systems related to the digital twin model in the present invention is a virtual environment.

[0062] The present invention discloses a distributed data acquisition system operation method, see Figure 1 , specifically including the following steps:

[0063] S1: Build a digital twin model of an industrial robot;

[0064] Specifically, there are usually two ways to geometrically model the digital twin model of an industrial robot. This involves directly selecting and importing the model according to the industrial robot model, or establishing a model (including workpiece and production line models) based on the actual geometric dimensions of the industrial robot. Furthermore, the digital twin model is given the same material as the actual industrial robot to ensure that the digital twin model is highly consistent with the actual industrial robot in terms of geometric dimensions, material properties, color, shape, etc., and has a visual "twin". At the same time, it can also truly reflect the assembly relationship, origin position, and subordinate relationship of the actual working environment of the industrial robot, and has a structural "twin".

[0065] S2: Establish a kinematic model of the industrial robot and perform forward kinematics analysis and inverse kinematics analysis on the established kinematic model;

[0066] Specifically, industrial robot models must be capable of motion simulation, meaning translational or rotational changes between links (depending on the robot's joint axis type). Therefore, parameters such as the positive direction of link motion, the selection rules for the reference coordinate system, and its offset must be consistent with the actual environment. The robot's trajectory planning process must satisfy kinematic constraints, expressed as interpolation of angles and velocities in joint space or interpolation of the end-effector's position in Cartesian space.

[0067] In order to determine the angles of each joint when the end effector is in a key point posture, the kinematic expression of the robot is analyzed, which includes the kinematic modeling process and the forward kinematics and inverse kinematics solution processes. The forward kinematics solution is to infer the homogeneous transformation matrix of the end effector coordinate system relative to the base coordinate system through the combination relationship (rotation angle) of each joint and link, so as to grasp the operating status of the robot in real time; and the inverse kinematics solution is the process of converting the point position in Cartesian space into the angle in joint space. Since robots often need to plan paths according to the posture in the Cartesian coordinate system when performing tasks in industrial sites, inverse kinematics solution occupies an important position in the trajectory planning process.

[0068] It should be noted that this embodiment takes a six-degree-of-freedom industrial robot as an example, see Figure 2 , specifically describing the method disclosed in the present invention.

[0069] There are two main methods for solving the inverse kinematics of six-axis robots: numerical method and analytical method. Among them, the numerical method needs to be implemented through iterative calculation. Due to the large amount of calculation, it is usually slower than the analytical method. The six-axis serial robot only needs to meet the Pieper criterion, and there is an analytical solution that meets the conditions. The classic DH parameter method is used to realize the establishment of the robot's forward kinematics model and the inverse kinematics solution process.

[0070] The specific solution is as follows:

[0071] The specific implementation of forward kinematics analysis is:

[0072] Forward kinematics analysis is to determine the position of the end effector when the joint angle, link length and combination of the robot are determined. The position of the end effector is determined by the homogeneous transformation matrix The specific expression is:

[0073]

[0074] in, Represents the poses of the six joint coordinate systems relative to the base coordinate system; Indicates the relative relationship between the i-th joint and the i-1 joint coordinate system; (n x ,n y ,n z) represents the x-axis direction of the end effector coordinate system; (o x ,o y ,o z ) represents the y-axis direction of the end effector coordinate system; (a x ,a y ,a z ) represents the z-axis direction of the end effector coordinate system; n, o, a are three orthogonal unit vectors describing the end effector posture, and these three vectors together constitute the rotation matrix of the end effector; (p x ,p y ,p z ) represents the position of the end effector;

[0075] Connecting rod length a i , connecting rod torsion angle α i , connecting rod offset d i , joint angle θ i Four parameters are used to describe the relative relationship between two adjacent rods, see Figure 3 , specifically: d i is the distance from the origin of the i-1 coordinate system to Z i-1 Axis and X i The intersection of the axes along the Z i-1 The distance measured along the axis; a i is the length of the common normal between the axis of joint i and the axis of joint i+1; α i The axis of joint i and the axis of joint i+1 are at the axis of joint i and a i The angle on the plane; θ i For Z i-1 Axis X i-1 Axis steering X i The joint angles of the axes, where i = 1, 2, ..., 6; the initial value represents the angles of each joint in the initial state of the industrial robot;

[0076] Through the above definition, the transformation relationship is expressed as a matrix express:

[0077]

[0078] Among them, Trans(X,l) represents translation transformation, that is, translation l units along the positive direction of the X axis; Rot(X,θ) represents rotation transformation, that is, rotation angle θ around the positive direction of the X axis;

[0079] Combine equations (1) and (2) to obtain the pose matrix of the end effector at the key point:

[0080] The inverse kinematics analysis is specifically implemented as follows:

[0081] Inverse kinematics refers to the pose matrix of the end effector Reverse solve the joint angle θ i (i=1,2,…,6);

[0082] Separate the expressions of the position and posture of the industrial robot, specifically:

[0083] Multiply the first three joint coordinate system transformation matrices in equation (1) by the left side:

[0084]

[0085] The matrices on both sides of equation (3) are divided into blocks and equalized to obtain the equation system:

[0086]

[0087] Among them, s i = sinθ i , c i =cosθ i ,s ij = sin(θ i +θ j )c ij =cos(θ i +θ j )(i=1,2,…,6)(j=1,2,…,6);

[0088] The arctan2(y / x) function is introduced to solve θ in equation (4) to obtain all 8 groups of solutions for the six joint angles:

[0089] Since the equations in formula (4) can be expressed as follows:

[0090] asinθ i +bcosθ i =c (5)

[0091] If a, b, c are continuous in this formula, and only if inequality a 2 +b 2 >c 2 When this is true, the equation has a solution:

[0092]

[0093] Combining equations (4), (5), and (6), we can obtain all 8 groups of solutions.

[0094] Because the deviations in the first three joint angles have a greater impact on the end effector, it is important to minimize the difference between the current angles of the first three joints and the angles at the previous keypoint. Least squares methods are used to select the optimal solution that satisfies these requirements, saving runtime and energy. All keypoint poses can be converted to joint angles using this method.

[0095] The principle of obtaining the optimal solution among the 8 groups of solutions obtained is:

[0096]

[0097] Among them, θ ij represents the jth group of solutions for the i-th joint, θ i ′ represents the angle of the i-th joint at the previous point.

[0098] S3: Associating the digital twin model of the industrial robot established in step S1 with the industrial robot signal to perform virtual debugging and digital twin virtual-reality mapping;

[0099] Specifically include:

[0100] S31: Using process simulation, the digital twin model is given process attributes, so that each process action of the industrial robot digital twin model has corresponding motion process logic;

[0101] Specifically, process simulation is used to give industrial robots process attributes, such as the opening and closing of fixtures and the clamping path when the industrial robot grasps parts, and the angle and angular velocity of the turntable during rotation, so that each process action of the industrial robot has corresponding motion process logic.

[0102] From the inverse kinematics of the robot, we can see that the mapping from the robot's end position to the joint position is very complex, especially for robots with multiple degrees of freedom, which sometimes may not have an analytical solution. Therefore, in order to prevent the generation of singular solutions, transition points can be appropriately added when defining the robot process.

[0103] For example, Figure 4 For example, the following points are set during the motion of an industrial robot:

[0104] The Home point is defined as a point where the robot is prevented from encountering a singularity during movement. The initial posture of the robot must be changed, and the new posture becomes the Home point of the robot. Transition point 1: A transition point is established between the industrial robot's Home point and the robot's grasping position point to prevent the robot from encountering a collision point or limit point during movement. Here, the robot is rotated 60° along the Z axis. Transition point 2: This point is generally set directly above the grasping point to align with the workpiece grasping position point. Grasping point: This point is where the robot grasps the workpiece. Via_5 point: This point is where the robot prevents collision with the machining center.

[0105] Therefore, the process of the industrial robot is set to move from the "Home point" to the "Transition point 1", then to the "Transition point 2", and finally to the "Grasping point". After the workpiece is grasped, it moves from the "Grasping point" to the "Transition point 2", then to the "Transition point 1", and finally to the "Home point". The process ensures that the robot's path is smooth.

[0106] S32: Use the timing editor to perform timing simulation on the process attributes of the industrial robot, and plan the timing relationship of each process according to the timing table of the action process;

[0107] Specifically, after the process attribute definition of the robot is completed, the timing editor is used to perform timing simulation. The timing relationship of each process is planned according to the timing table of the action process, and the rationality of the production process is verified through process timing simulation. Preferably, the process timing simulation is a time-based simulation, see Figure 5 .

[0108] S33: Realize the synchronous mapping between industrial robots and their digital twin models:

[0109] Establish real-time communication between industrial robots and their digital twins;

[0110] Specifically, the communication between the industrial robot and the virtual environment uses the TCP / IP protocol, and the network programming interface Socket is used to transmit the robot's real-time joint data. Applying steps 1 and 2 in the virtual model can achieve the synchronous movement of the digital twin model and bind the virtual digital twin model with the real data.

[0111] When the control unit of the industrial robot serves as the communication server, virtual reality is reflected in the real world: the industrial robot transmits its joint data to its digital twin model in real time, and its digital twin model receives the joint data transmitted by the industrial robot and applies steps S1 and S2 to achieve synchronous motion.

[0112] When the control unit of the digital twin model is used as the communication server, virtual control of the real is achieved: the digital twin model sends control instructions to the control unit of the industrial robot, and the industrial robot receives and executes the control instructions;

[0113] Preferably, real-time collected data is divided into two categories: real-time position data and real-time signal data. Real-time position data includes but is not limited to the real-time joint angles, joint speeds, and end-positions of industrial robots during movement; real-time signal data includes but is not limited to PLC signals; signal configuration mainly includes signal name, type, address, serial number, controlled model ID, IEC format, etc.; the signal connection process is mainly divided into creating new signals, signal parameter configuration, signal type definition, setting model resources, setting signal addresses, logical linkage, and digital twins, see Figure 6 .

[0114] S4: Industrial robots realize digital twin visualization.

[0115] Specifically, after the kinematic definition, process simulation, processing timing simulation, and data signal connection of the industrial robot model, the scene with behavioral logic properties and capable of being driven by actual real-time data signals is published as a digital twin scene through the digital twin scene, realizing the digital twin effect of real-time dynamic mapping of the industrial robot's action status.

[0116] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0117] The above embodiments are merely descriptions of preferred implementations of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary engineers and technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A virtual debugging and simulation method for industrial robots based on digital twins, characterized in that: The following steps are involved: S1: Build a digital twin model of an industrial robot; S2: Establish a kinematic model of the industrial robot and perform forward kinematics analysis and inverse kinematics analysis on the established kinematic model; S3: Associating the digital twin model of the industrial robot established in step S1 with the industrial robot signal to perform virtual debugging and digital twin virtual-reality mapping; S4: Digital twin visualization of industrial robots; The specific implementation of step S1 is: Directly import the industrial robot model or build a model based on the actual geometric dimensions of the industrial robot; Set the geometric model to have the same material, color, shape, and structure as the industrial robot, so that the generated digital twin model has a visual and structural twin relationship with the industrial robot; The forward kinematics analysis in step S2 is specifically implemented as follows: Forward kinematics analysis is to determine the position of the end effector when the joint angle, link length and combination of the robot are determined. The position of the end effector is determined by the homogeneous transformation matrix The specific expression is: in, Represents the poses of the six joint coordinate systems relative to the base coordinate system; Indicates the relative relationship between the i-th joint and the i-1 joint coordinate system; (n x ,n y ,n z ) represents the x-axis direction of the end effector coordinate system; (o x ,o y ,o z ) represents the y-axis direction of the end effector coordinate system; (a x ,a y ,a z ) represents the z-axis direction of the end effector coordinate system; (p x ,p y ,p z ) represents the position of the end effector; Connecting rod length a i , connecting rod torsion angle α i , connecting rod offset d i , joint angle θ i Four parameters are used to describe the relative relationship between two adjacent rods, specifically: d i is the distance from the origin of the i-1 coordinate system to Z i-1 Axis and X i The intersection of the axes along the Z i-1 The distance measured along the axis; a i is the length of the common normal between the axis of joint i and the axis of joint i+1; α i The axis of joint i and the axis of joint i+1 are at the axis of joint i and a i The angle on the plane; θ i For Z i-1 Axis X i-1 Axis steering X i The joint angles of the axes, where i = 1, 2, ..., 6; the initial value represents the angles of each joint in the initial state of the industrial robot; Through the above definition, the transformation relationship is expressed as a matrix express: Among them, Trans(X,l) represents translation transformation, that is, translation l units along the positive direction of the X axis; Rot(X,θ) represents rotation transformation, that is, rotation angle θ around the positive direction of the X axis; Combine equations (1) and (2) to obtain the pose matrix of the end effector at the key point: The inverse kinematics analysis in step S2 is specifically implemented as follows: Inverse kinematics refers to the pose matrix of the end effector Reverse solve the angle θ of each joint i (i=1,2,…,6); Separate the expressions of the position and posture of the industrial robot, specifically: Multiply the first three joint coordinate system transformation matrices in equation (1) by the left side: The matrices on both sides of equation (3) are divided into blocks and equalized to obtain the equation system: among them, s i =sinθ i ,c i =cosθ i ,s ij =sin(θ i +θ j ),c ij =cos(θ i +θ j )(i=1,2,…,6)(j=1,2,…,6); The arctan2(y / x) function is introduced to solve θ in equation (4) to obtain all 8 groups of solutions for the six joint angles: Since the equations in formula (4) can be expressed as follows: a sinθ i +b cosθ i =c (5) If a, b, c are continuous in this formula, and only if inequality a 2 +b 2 >c 2 When this is true, the equation has a solution: Combine equations (4)(5)(6) to obtain all 8 groups of solutions; The principle of obtaining the optimal solution among the 8 groups of solutions obtained is: Among them, θ ij represents the jth group of solutions for the i-th joint, θ i 'Indicates the angle of the i-th joint at the previous point.

2. The method for virtual debugging and simulation of an industrial robot based on digital twin according to claim 1, characterized in that: The specific implementation of step S3 includes: By using process simulation methods, the digital twin model is given process attributes, so that each process action of the digital twin model of the industrial robot has corresponding motion process logic; Use the timing editor to simulate the process properties of the industrial robot and plan the timing relationship of each process according to the timing table of the action process; Achieve synchronous mapping between industrial robots and their digital twin models: Establish real-time communication between industrial robots and their digital twins; When the control unit of the industrial robot serves as the communication server, virtual reality is reflected in the real world: the industrial robot transmits its joint data to its digital twin model in real time, and its digital twin model receives the joint data transmitted by the industrial robot and applies steps S1 and S2 to achieve synchronous motion. When the control unit of the digital twin model is used as the communication server, virtual control of the real is achieved: the digital twin model sends control instructions to the control unit of the industrial robot, and the industrial robot receives and executes the control instructions.

3. The method for virtual debugging and simulation of an industrial robot based on digital twin according to claim 2, characterized in that: Timing simulation of industrial robots is a time-based simulation.

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